一、主要内容 创建新变量 修改数据 修改变量名 处理缺失值 数据排序 数据合并 数据筛选 抽样
二、R语言代码
rm(list=ls()) gc() manager <- c(1,2,3,4,5) date <- c("10/24/08", "10/28/08", "10/1/08", "10/12/08", "5/1/09") country <- c("US", "US", "UK", "UK", "UK") gender <- c("M", "F", "F", "M", "F") age <- c(32,45,25,39,99) q1 <- c(5,3,3,3,2) q2 <- c(4,5,5,3,2) q3 <- c(5,2,5,4,1) q4 <- c(5,5,5,NA,2) q5 <- c(5,5,2,NA,1) leadership <- data.frame(manager, date ,country, gender, age, q1,q2,q3,q4,q5, stringsAsFactors=F) ############创建新变量 leadership <- transform(leadership,meanx= (q1+q2+q3+q4+q5)/5) ############修改数据 leadership$age[leadership$age==99] <- NA leadership$agecat2 <- NA leadership <- within(leadership,{ agecat2[age>75] <- "Elder" agecat2[age>=55 & age<=75] <- "Middle Aged" agecat2[age<55] <- "Young"} ) #####################修改变量名################# library(plyr) leadership <- rename(leadership,c(manager="managerID", date="testDate")) ##################处理缺失值################ (leadership <- transform(leadership,meanx=rowMeans(leadership[6:10],na.rm=T))) options(digits=3)###设置有效数字 ###################数据排序############### leadership[order(age),] leadership[order(gender,age),] leadership[order(gender,-age),] ####################数据合并############### manager <- c(1,2,3,4,5) q6 <- c(4,3,4,2,1) leadership2 <- data.frame(manager,q6) leadership2 merge(leadership,leadership2,by.x ="managerID",by.y = "manager") ######################数据筛选############# leadership[,c(6:10)] leadership[c("q1","q2","q3","q4","q5")] myvars <- paste("q",1:5,sep="") (newdata <- leadership[myvars]) leadership[gender=='M' & age>30,] subset(leadership, age>=35 | age<24, select=gender:q4) #####################抽样######################## leadership[sample(1:nrow(leadership),3,replace=F),]